(145 days)
Not Found
Yes
The document explicitly mentions "machine learning algorithms" and describes the training and testing data used for these algorithms, specifically for "Left Heart Segmentation" and "Landing Zone Detection".
No.
The device is a software application for pre-procedural planning and post-procedural evaluation, providing visualization, measurement, and reporting tools. It does not directly treat or prevent a disease, nor does it restore, modify, or correct a body function. Its purpose is to aid physicians in assessment and planning, not to provide therapy itself.
Yes
Explanation: The device is used for pre-procedural planning, sizing, and post-procedural evaluation, which are activities directly related to diagnosing or assessing medical conditions and planning interventions based on that assessment. It provides "anatomical assessment" and helps determine "size of a closure device needed," which is inherently diagnostic in nature.
Yes
The device description explicitly states "The TruPlan Computed Tomography (CT) Imaging Software application ("TruPlan") is a software as a medical device". The summary focuses entirely on the software's functionality, algorithms, and performance validation using existing CT data, with no mention of accompanying hardware components.
Based on the provided information, this device is NOT an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are medical devices intended for use in vitro for the examination of specimens, including blood, tissue, and urine, derived from the human body, solely or principally for the purpose of providing information concerning a physiological or pathological state, or concerning a congenital abnormality, or to determine the safety and compatibility with potential recipients, or to monitor therapeutic measures.
- TruPlan's Function: TruPlan is a software application that processes medical images (CT scans) of the heart and vessels. It provides tools for visualization, measurement, and planning based on these images. It does not analyze biological specimens (blood, tissue, etc.) taken from the patient.
- Intended Use: The intended use is for pre- and post-procedural planning and evaluation of the Left Atrial Appendage Closure (LAAC) procedure using CT data. This is an image-based assessment, not a diagnostic test performed on a biological sample.
Therefore, TruPlan falls under the category of medical imaging software or a medical device software, but not an In Vitro Diagnostic device.
No
The provided text does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The text only includes "Control Plan Authorized (PCCP) and relevant text: Not Found".
Intended Use / Indications for Use
TruPlan Computed Tomography (CT) Imaging Software
Indications for Use (Describe)
TruPlan enables visualization and measurement of structures of the heart and vessels for:
- · Pre-procedural planning and sizing for the left atrial appendage closure (LAAC) procedure
- · Post-procedural evaluation for the LAAC procedure
To facilitate the above, TruPlan provides general functionality such as:
- · Segmentation of cardiovascular structures
- · Visualization and image reconstruction techniques: 2D review, Volume Rendering, MPR
- · Simulation of TEE views, ICE views, and fluoroscopic rendering
- · Measurement and annotation tools
- · Reporting tools
TruPlan's intended patient population is comprised of adult patients.
Product codes (comma separated list FDA assigned to the subject device)
QIH, LLZ
Device Description
The TruPlan Computed Tomography (CT) Imaging Software application ("TruPlan") is a software as a medical device that helps qualified users with image-based pre-procedural planning and post-procedural follow-up of the Left Atrial Appendage Closure (LAAC) procedure using CT data. TruPlan is designed to support the anatomical assessment of the Left Atrial Appendage (LAA) prior to and following the LAAC procedure. This includes the assessment of the LAA size, shape, and relationships with adjacent cardiac and extracardiac structures. This assessment helps the physician determine the size of a closure device needed for the LAAC procedure and evaluate LAAC device placement in a follow-up CT study. The TruPlan application is a visualization software and has basic measurement tools. The device is intended to be used as an aid to the existing standard of care and does not replace existing software applications physicians use for planning or follow-up for a LAAC procedure.
Pre-existing CT images are uploaded in TruPlan manually by the end-user. The images can be viewed by the user in the original CT image as well as simulated views. The software displays the views in a modular format as follows:
- Left Atrial Appendage (LAA) .
- Fluoroscopy (Fluoro, simulation) ●
- Trans Esophageal Echo (TEE, simulation) ●
- Intra Cardiac Echography (ICE, simulation) ●
- . Thrombus
- Follow-up
- Multiplanar Reconstruction (MPR)
- Reporting ●
These views offer the user visualization and quantification capabilities for pre-procedural planning and post-procedural follow-up of the LAAC procedure; none are intended for diagnosis. The quantification tools are based on user-identified regions of interest and are user-modifiable. The device allows users to perform the measurements (all done on MPR viewers) listed in Table 1, below.
TruPlan also provides reporting functionality to capture screenshots and measurements and to store them as a PDF document.
TruPlan is installed either as a standalone software onto the user's desktop or laptop computer, or as a server within the hospital infrastructure with a thick-client software on multiple users' desktop or laptop computers.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CT data in DICOM format
Anatomical Site
Heart and vessels, specifically Left Atrial Appendage (LAA)
Indicated Patient Age Range
Adult patients
Intended User / Care Setting
Qualified users/physicians, hospital infrastructure (standalone software or server with thick-client)
Description of the training set, sample size, data source, and annotation protocol
The data used to train TruPlan's machine learning algorithms were sourced from multiple clinical sites from urban centers and from different countries. The Left Heart Segmentation algorithm was trained on a total of 113 cases from the U.S., Canada, Germany, and other locations acquired using Siemens, GE, Toshiba, and Philips scanners where the left heart structures were manually annotated by multiple expert readers. The Landing Zone Detection algorithm was trained on a total of 273 cases from various sites across the U.S. acquired using Siemens, GE, Toshiba, and Philips scanners where the landing zone was manually contoured by expert readers.
When selecting data for training, the importance of model generalization was considered and data was selected such that a good distribution of patient demographics, scanner, and image parameters were represented. The separation into training versus validation datasets is made on the study level to ensure no overlap between the two sets. As such, different scans from the same study were not split between the training and validation datasets. None of the cases used for model validation were used for training the machine learning models.
Description of the test set, sample size, data source, and annotation protocol
Validation of Machine Learning Derived Outputs:
The machine learning algorithms of TruPlan (left heart segmentation, landing zone detection) have been trained and tested on images acquired from major vendors of CT imaging devices. All data used for validation were not used during the development of the training algorithms.
Across all CT machine manufacturers, n = 633 anonymized patient images were used for the validation of TruPlan. This translates into 533 samples (age and sex information unknown due to anonymization) for Left Heart Segmentation, and 100 samples (59 male and 41 female samples acquired from patients between 56 to 90+ years of age) for Landing Zone Detection. Image information for all samples was anonymized and limited to ePHI-free DICOM headers. The validation data was sourced from multiple sites across the U.S. and other urban regions.
For the Left Heart Segmentation algorithm, the validation data was collected from the U.S., Canada, South America, Europe, and Asia acquired using Siemens, GE, Toshiba, and Philips scanners.
For the Landing Zone Detection algorithm, the validation data was collected from various sites across the U.S., acquired using Siemens, GE, Toshiba, and Philips scanners. The landing zone was manually contoured by multiple expert readers for evaluation.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Validation of Machine Learning Derived Outputs:
Study Type: Performance Validation of Machine Learning Derived Outputs
Sample Size:
Left Heart Segmentation: 533 anonymized patient images (age and sex unknown)
Landing Zone Detection: 100 anonymized patient images (59 male, 41 female, ages 56-90+)
Key Results:
For the Left Heart Segmentation algorithm, the performance acceptance criteria were predefined to evaluate the performance of the ML model based on segmentation accuracy defined by probability of bone removal and probability of LAA visualization. Bone was removed in 532/533 cases (99.81%); the LAA was correctly visualized by the rendering algorithm in 519/533 cases (97.37%).
For the Landing Zone Detection algorithm, the performance acceptance criteria were predefined to evaluate the performance of the ML model based on detection accuracy defined by plane and contour center distance. Landing zone plane distance was within 10 mm in 97/100 cases (97%) with a mean distance of 3.87 mm; the landing zone contour center distance was within 12 mm in 99/100 cases (99%) with a mean distance of 2.92 mm.
All performance testing results met Circle's pre-defined acceptance criteria.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Left Heart Segmentation: Probability of bone removal (99.81%), probability of LAA visualization (97.37%).
Landing Zone Detection: Landing zone plane distance within 10 mm (97%), mean distance (3.87 mm); landing zone contour center distance within 12 mm (99%), mean distance (2.92 mm).
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
Circle Cardiovascular Imaging, Inc. % Sydney Toutant Regulatory Affairs Lead Suite 1100 - 800 5th Ave. SW Calgary, Alberta T2P 3T6 CANADA
January 18, 2023
Re: K222593
Trade/Device Name: TruPlan Computed Tomography (CT) Imaging Software Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH, LLZ Dated: December 9, 2022 Received: December 9, 2022
Dear Sydney Toutant:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for
1
devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director Imaging Software DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K222593
Device Name
TruPlan Computed Tomography (CT) Imaging Software
Indications for Use (Describe)
TruPlan enables visualization and measurement of structures of the heart and vessels for:
- · Pre-procedural planning and sizing for the left atrial appendage closure (LAAC) procedure
- · Post-procedural evaluation for the LAAC procedure
To facilitate the above, TruPlan provides general functionality such as:
- · Segmentation of cardiovascular structures
- · Visualization and image reconstruction techniques: 2D review, Volume Rendering, MPR
- · Simulation of TEE views, ICE views, and fluoroscopic rendering
- · Measurement and annotation tools
- · Reporting tools
TruPlan's intended patient population is comprised of adult patients.
| Type of Use (Select one or both, as applicable) |
|---|
| ------------------------------------------------- |
X Prescription Use (Part 21 CFR 801 Subpart D)
| Over-The-Counter Use (21 CFR 801 Subpart C)
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3
Image /page/3/Picture/1 description: The image contains the logo for Circle Cardiovascular Imaging. The logo features two incomplete circles, one larger and green, and one smaller and yellow, positioned above the word "circle" in gray lowercase letters. Below "circle" are the words "CARDIOVASCULAR IMAGING" in smaller, uppercase gray letters. The overall design is clean and professional, suggesting a focus on medical imaging technology.
The following 510(k) summary of safety and effectiveness information is submitted in accordance with the requirements of the Safe Medical Device Act 1990 and 21 CFR 807.92(c).
l. SUBMITTER
| Submitter's Name: | Circle Cardiovascular Imaging, Inc. |
|---|---|
| Address: | Suite 1100 – 800 5th Ave SW, Calgary, AB, Canada, T2P 3T6 |
| Date Prepared: | January 16 2023 |
| Telephone Number: | +1 587 747 4692 |
| Contact Person : | Sydney Toutant |
| Email: | sydney.toutant@circlecvi.com |
II. DEVICE
| Name of the Device: | TruPlan Computed Tomography (CT) Imaging Software |
|---|---|
| Short Brand Name: | TruPlan |
| Common or Usual Name: | Automated Radiological Image Processing System |
| Classification Name: | Medical image management and processing system |
| Proposed Classification: | Device Class: II |
| Primary Product Code: QIH | |
| Secondary Product Code: LLZ | |
| Regulation Number: 21 CFR 892.2050 |
PREDICATE DEVICES lll.
The primary predicate is the previously cleared version of TruPlan, manufactured by Circle CVI and cleared under K202212. 3mensio Workstation, manufactured by Pie Medical Imaging and cleared under K153736, is used as a secondary predicate.
The predicate devices have not been subject to a design-related recall.
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IV. DEVICE DESCRIPTION
The TruPlan Computed Tomography (CT) Imaging Software application ("TruPlan") is a software as a medical device that helps qualified users with image-based pre-procedural planning and post-procedural follow-up of the Left Atrial Appendage Closure (LAAC) procedure using CT data. TruPlan is designed to support the anatomical assessment of the Left Atrial Appendage (LAA) prior to and following the LAAC procedure. This includes the assessment of the LAA size, shape, and relationships with adjacent cardiac and extracardiac structures. This assessment helps the physician determine the size of a closure device needed for the LAAC procedure and evaluate LAAC device placement in a follow-up CT study. The TruPlan application is a visualization software and has basic measurement tools. The device is intended to be used as an aid to the existing standard of care and does not replace existing software applications physicians use for planning or follow-up for a LAAC procedure.
Pre-existing CT images are uploaded in TruPlan manually by the end-user. The images can be viewed by the user in the original CT image as well as simulated views. The software displays the views in a modular format as follows:
- Left Atrial Appendage (LAA) .
- Fluoroscopy (Fluoro, simulation) ●
- Trans Esophageal Echo (TEE, simulation) ●
- Intra Cardiac Echography (ICE, simulation) ●
- . Thrombus
- Follow-up
- Multiplanar Reconstruction (MPR)
- Reporting ●
These views offer the user visualization and quantification capabilities for pre-procedural planning and post-procedural follow-up of the LAAC procedure; none are intended for diagnosis. The quantification tools are based on user-identified regions of interest and are user-modifiable. The device allows users to perform the measurements (all done on MPR viewers) listed in Table 1, below.
TruPlan implements machine learning techniques to aid device use as follows:
-
- Left Heart Segmentation. TruPlan generates a 3D rendering of the left side of the heart (including left ventricle, left atrium, and LAA) using machine learning methodology. The 3D rendering is for visualization purposes only; no measurement or annotations can be done using this view.
-
- Landing Zone Detection. TruPlan uses machine learning techniques to initialize landing zone detection. No measurements are computed until the user reviews and corrects this initialization.
The data used to train TruPlan's machine learning algorithms were sourced from multiple clinical sites from urban centers and from different countries. The Left Heart Segmentation algorithm was trained on a total of 113 cases from the U.S., Canada, Germany, and other locations acquired using Siemens, GE, Toshiba, and Philips scanners where the left heart structures were manually
Circle Cardiovascular Imaging Inc.
5
annotated by multiple expert readers. The Landing Zone Detection algorithm was trained on a total of 273 cases from various sites across the U.S. acquired using Siemens, GE, Toshiba, and Philips scanners where the landing zone was manually contoured by expert readers.
When selecting data for training, the importance of model generalization was considered and data was selected such that a good distribution of patient demographics, scanner, and image parameters were represented. The separation into training versus validation datasets is made on the study level to ensure no overlap between the two sets. As such, different scans from the same study were not split between the training and validation datasets. None of the cases used for model validation were used for training the machine learning models.
Table 1. TruPlan's measurement functionality and the specific module/workflow and measurement application for which it is used.
| Measurement [units] | Description | Module / Workflow | Application |
|---|---|---|---|
| Distance [mm] | Length between two points, | ||
| for both curved lines | |||
| (splines) and straight lines, | |||
| including the diameter | |||
| (including min, max, | |||
| average) resulting from | |||
| closed splines and depth of | |||
| the LAA | All modules | Diameter & depth of LAA | |
| landing zone (LAA module); | |||
| distance between points of | |||
| interest; diameter of a peri- | |||
| device leak (Follow-up | |||
| module) | |||
| Perimeter [mm] | The perimeter of a contour | ||
| (closed spline) | All modules | Perimeter of LAA landing zone | |
| (LAA module); perimeter of | |||
| other contours of interest | |||
| Area [mm²] | The area within a contour | All modules | Area of LAA landing zone |
| (LAA module); area of other | |||
| contours | |||
| of interest | |||
| Angle [degrees] | The angle of an object / | ||
| structure of interest | All modules | Angle between two lines of | |
| interest | |||
| Signal intensity | |||
| [HU] | Hounsfield value (in | ||
| Hounsfield Units, HU) of the | |||
| underlying pixels | All modules | Signal intensity of pixels in the | |
| regular vs. delayed scan | |||
| (Thrombus module); average | |||
| signal intensity within distal | |||
| LAA (Follow-up module); | |||
| intensity of other pixels of | |||
| interest | |||
| Coordinates | |||
| [mm, mm, mm] | Location in the x-, y-, and z- | ||
| planes of a point | All modules | Coordinates of points of | |
| interest on a 3D rendering, | |||
| for export purposes |
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These measurements are all manually placed by the user as annotations (overlays) and report the information calculated using the underlying pixels. TruPlan also provides reporting functionality to capture screenshots and measurements and to store them as a PDF document.
TruPlan is installed either as a standalone software onto the user's desktop or laptop computer, or as a server within the hospital infrastructure with a thick-client software on multiple users' desktop or laptop computers.
V. INDICATIONS FOR USE
TruPlan enables visualization and measurement of structures of the heart and vessels for:
- Pre-procedural planning and sizing for the left atrial appendage closure (LAAC) . procedure
- Post-procedural evaluation for the LAAC procedure
To facilitate the above, TruPlan provides general functionality such as:
- Segmentation of cardiovascular structures ●
- . Visualization and image reconstruction techniques: 2D review, Volume Rendering, MPR
- Simulation of TEE views, ICE views, and fluoroscopic rendering ●
- Measurement and annotation tools
- Reporting tools ●
TruPlan's intended patient population is comprised of adult patients.
Image /page/6/Picture/14 description: The image shows a yellow warning sign. The sign is in the shape of a triangle with a thick black border. Inside the triangle is a large black exclamation point.
IMPORTANT: TruPlan is intended to be used as a pre-procedural planning aid, and LAAC procedures should be performed per the chosen LAAC device's approved IFU.
Image /page/6/Picture/16 description: The image shows a yellow triangle with a black exclamation point inside. The triangle is a warning sign, indicating a potential hazard or danger. The exclamation point emphasizes the importance of the warning. The sign is commonly used to alert people to be cautious and pay attention to their surroundings.
IMPORTANT: TruPlan is intended to be used as a post-procedural assessment aid, and all clinical decisions should be made per the chosen LAAC device's approved IFU.
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VI. COMPARISON WITH PREDICATE DEVICES
The detailed analysis of the subject device and the primary and secondary predicate devices (shown in Table 2 and Table 3) demonstrates that the subject device is substantially equivalent in indications for use / intended use, technological characteristics, functionality, and operating principles with the primary predicate (K202212) and with the secondary predicate (K153736). Of the three characteristics (technical, biological, and clinical) required for the demonstration of equivalence, biological characteristics are not applicable since the subject device and both predicate devices are software as a medical device application with no tangible component interfacing with the body.
| Subject Device | Primary Predicate | Secondary Predicate |
|---|---|---|
| TruPlan v3.0 (K222593) | TruPlan v1.0 (K202212) | 3mensio (K153736) |
| Manufactured by Circle | Manufactured by Circle | Manufactured by Pie Medical Imaging |
| TruPlan enables visualization and | ||
| measurement of structures of the heart | ||
| and vessels for: | TruPlan enables visualization and | |
| measurement of structures of the heart | ||
| and vessels for pre-procedural planning | ||
| and sizing for the left atrial appendage | ||
| closure (LAAC) procedure. | 3mensio Workstation enables visualization | |
| and measurement of structures of the | ||
| heart and vessels for: | ||
| • Pre-procedural planning and sizing for | ||
| the left atrial appendage closure | ||
| (LAAC) procedure | To facilitate the above, TruPlan provides | |
| general functionality such as: | • Pre-operational planning and sizing | |
| for cardiovascular interventions and | ||
| surgery | ||
| • Post-procedural evaluation for the | ||
| LAAC procedure | • Segmentation of cardiovascular | |
| structures | • Postoperative evaluation | |
| To facilitate the above, TruPlan provides | ||
| general functionality such as: | • Visualization and image | |
| reconstruction techniques: 2D review, | ||
| Volume Rendering, MPR | • Support of clinical diagnosis by | |
| quantifying dimensions in coronary | ||
| arteries | ||
| • Segmentation of cardiovascular | ||
| structures | • Simulation of TEE views, ICE views, | |
| and fluoroscopic rendering | • Support of clinical diagnosis by | |
| quantifying calcifications (calcium | ||
| scoring) in the coronary arteries | ||
| • Visualization and image | ||
| reconstruction techniques: 2D review, | ||
| Volume Rendering, MPR | • Measurement and annotation tools | To facilitate the above, 3mensio |
| Workstation provides general functionality | ||
| such as: | ||
| • Simulation of TEE views, ICE views, | ||
| and fluoroscopic rendering | • Reporting tools | • Segmentation of cardiovascular |
| structures | ||
| • Measurement and annotation tools | TruPlan's intended patient population is | |
| comprised of adult patients. | • Automatic and manual centerline | |
| detection | ||
| • Reporting tools | • Visualization and image | |
| reconstruction techniques: 2D review, | ||
| Volume Rendering, MPR, Curved | ||
| MPR, Stretched CMPR, Slabbing, | ||
| MIP, AIP, MinIP | ||
| TruPlan's intended patient population is | ||
| comprised of adult patients. | • Measurement and annotation tools | |
| • Reporting tools |
| Table 2. Indications for Use comparison to predicate devices. | |||
|---|---|---|---|
| Feature | Subject Device | Primary Predicate | Secondary Predicate |
| TruPlan v3.0 (K222593) | TruPlan v1.0 (K202212) | 3mensio (K153736) | |
| Manufactured by Circle | Manufactured by Circle | Manufactured by Pie Medical | |
| Device Class | II | II | II |
| Device Classification | QIH | ||
| LLZ | LLZ | LLZ | |
| Regulation Name | Medical image management and | ||
| processing system | Picture Archiving and | ||
| Communications System | Picture Archiving and | ||
| Communications System | |||
| Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 |
| Input data type | CT data in DICOM format (vendor | ||
| independent) | CT data in DICOM format (vendor | ||
| independent) | CT data in DICOM (vendor | ||
| independent) | |||
| Landing Zone | |||
| Detection | Semi-automatic initialization of the | ||
| landing zone using Machine | |||
| Learning techniques; manual | |||
| confirmation of the landing zone | Manual initialization and | ||
| confirmation of the landing zone | Manual initialization and | ||
| confirmation of the landing zone | |||
| Left Heart | |||
| Segmentation | Semi-automatic segmentation for | ||
| 3D visualization of the left heart | |||
| using Machine Learning | |||
| techniques; manual editing of 3D | |||
| views possible | Semi-automatic segmentation for | ||
| 3D visualization of the left heart | |||
| using Machine Learning | |||
| techniques; manual editing of 3D | |||
| views possible | Semi-automatic segmentation for | ||
| 3D visualization of the left heart; | |||
| manual editing of 3D views possible | |||
| Study list image | |||
| functionality | Study/series previewing Exporting Deleting Anonymizing Search | Study/series previewing Exporting Deleting Anonymizing Search | Study/series previewing Exporting Deleting Anonymizing Search |
| Image assessment – | |||
| simulated views | Fluoroscopy (grayscale 3D | ||
| rendering), to visualize | |||
| relationship among LAAC | |||
| procedure relevant | |||
| anatomical structures TEE, to provide similar views | |||
| to intraprocedural TEE ICE, to provide similar views | |||
| to intraprocedural ICE | Fluoroscopy (grayscale 3D | ||
| rendering), to visualize | |||
| relationship among LAAC | |||
| procedure relevant | |||
| anatomical structures TEE, to provide similar views | |||
| to intraprocedural TEE ICE, to provide similar views | |||
| to intraprocedural ICE | Grayscale 3D rendering, to | ||
| visualize relationship among | |||
| LAAC procedure relevant | |||
| anatomical structures TEE, to provide similar views to | |||
| intraprocedural TEE | |||
| Image assessment – | |||
| other visualization | |||
| functionality | 2D 3D (with manual & semi- | ||
| automatic segmentation) 4D (cine) MPR Annotations | 2D 3D (with manual & semi- | ||
| automatic segmentation) 4D (cine) MPR Annotations | 2D 3D (with manual & semi- | ||
| automatic segmentation) 4D (cine) MPR Annotations Curved MPR Stretch CMPR Slabbing MIP AIP MinIP Centreline extraction Calcium coring | |||
| Image assessment – | |||
| measurement | |||
| functionality | Distance (length, diameter, | ||
| perimeter) Area Angle Signal intensity Coordinates | Distance (length, diameter, | ||
| perimeter) Area Angle Signal intensity Coordinates | Distance (length, diameter, | ||
| perimeter) Area Angle Signal intensity Coordinates Volume | |||
| Report functionality | Patient/study information | Patient/study information | Patient/study information |
| Feature | Subject Device | Primary Predicate | Secondary Predicate |
| TruPlan v3.0 (K222593) | TruPlan v1.0 (K202212) | 3mensio (K153736) | |
| Manufactured by Circle | Manufactured by Circle | Manufactured by Pie Medical | |
| Screenshots | Screenshots | Screenshots | |
| ● | ● | ● | |
| Measurements | Measurements | Measurements | |
| ● | ● | ● | |
| Free text | Free text | Free text | |
| ● | ● | ● | |
| Device sizing table (for | Device sizing table (for | Device-specific reports for | |
| reference only) for LAA | reference only) for LAA | procedures covered in intended | |
| procedure | procedure | use | |
| Operating system | Microsoft Windows | ||
| Apple macOS | Microsoft Windows | Microsoft Windows | |
| DICOM compliant | Yes | Yes | Yes |
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Table 3. Feature comparison to primary and secondary predicate devices.
Circle Cardiovascular Imaging Inc.
Non-Confidential
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VII. PERFORMANCE DATA AND TESTING
Performance testing was conducted to verify compliance with specified design requirements in accordance with ISO 13485:2016, IEC 62304:2015, ISO 14971:2019, and NEMA 3.1-3.20 (2016) DICOM standards.
Verification and validation testing were conducted to ensure specifications and performance of the device and were performed per the FDA Guidance documents "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" and "Content of Premarket Submission for Management of Cybersecurity in Medical Devices". No clinical studies were necessary to support substantial equivalence.
TruPlan has been tested according to the specifications that are documented in a Master Software Test Plan. Testing is an integral part of Circle Cardiovascular Imaging Inc.'s software development as described in the company's product development process.
Validation of Machine Learning Derived Outputs
The machine learning algorithms of TruPlan (left heart segmentation, landing zone detection) have been trained and tested on images acquired from major vendors of CT imaging devices. All data used for validation were not used during the development of the training algorithms.
Across all CT machine manufacturers, n = 633 anonymized patient images were used for the validation of TruPlan. This translates into 533 samples (age and sex information unknown due to anonymization) for Left Heart Segmentation, and 100 samples (59 male and 41 female samples acquired from patients between 56 to 90+ years of age) for Landing Zone Detection. Image information for all samples was anonymized and limited to ePHI-free DICOM headers. The validation data was sourced from multiple sites across the U.S. and other urban regions. All performance testing results met Circle's pre-defined acceptance criteria.
- . For the Left Heart Segmentation algorithm, the performance acceptance criteria were predefined to evaluate the performance of the ML model based on seqmentation accuracy defined by probability of bone removal and probability of LAA visualization. The validation data was collected from the U.S., Canada, South America, Europe, and Asia acquired
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using Siemens, GE, Toshiba, and Philips scanners. Bone was removed in 532/533 cases (99.81%); the LAA was correctly visualized by the rendering algorithm in 519/533 cases (97.37%).
- For the Landing Zone Detection algorithm, the performance acceptance criteria were pre-. defined to evaluate the performance of the ML model based on detection accuracy defined by plane and contour center distance. The validation data was collected from various sites across the U.S., acquired using Siemens, GE, Toshiba, and Philips scanners. The landing zone was manually contoured by multiple expert readers for evaluation. Landing zone plane distance was within 10 mm in 97/100 cases (97%) with a mean distance of 3.87 mm; the landing zone contour center distance was within 12 mm in 99/100 cases (99%) with a mean distance of 2.92 mm.
VIII. CONCLUSIONS
The information submitted in this premarket notification, including the performance testing and predicate device comparisons, support the safety and effectiveness of TruPlan as compared to the predicate devices when used for the defined intended use.